The importance of managing organizational knowledge of enterprises has been recognized for decades. The systematic development and reuse of organizational knowledge is expected to improve the competitiveness of the enterprise. While the practice of “reuse” is common in general computer science there is still a lack of surveys in regard to reuse in enterprise modeling. This document reviews four different papers presented at information systems conferences over the last seven years: CAISE, EMMSAD, ICIS, and INCOM. Our analysis indicates that the majority of research is realized by case studies, theoretical frameworks and mostly on business process modeling aspects of enterprise models.

Research projects have an inherent risk of failure, and learning howto cope with the risk is an important task for everyone involved. In order to doso it is necessary to share the knowledge of the experiences done during andafter the project. This paper investigates a recently completed enterprisemodeling research project and contributes with lessons learned andrecommendations for future enterprise modeling projects.

Nowadays, IT operations devolve many tasks in IT services to internal customers (i.e., IT self-service). The rationale for this service task devolvement is often to reduce the IT personnel’s workload. However, prior research has shown that IT operations often fail to achieve this goal. Existing methods for modeling and analyzing services fall short of supporting service providers in identifying and specifying service tasks suitable to be devolved to (internal) customers. This paper presents, therefore, the first method for devolving service tasks in IT services (DESERV IT). DESERV IT is a compound of four method components encompassing a joint meta-model, a visual notation for modeling IT services, and procedural recommendations. The DESERV IT meta-model extends the meta-model of service blueprinting by means of concepts required to analyze service task devolvement. DESERV IT is evaluated in four evaluation episodes. The results of the evaluation episodes show that DESERV IT is perceived as effective, useful, complete, and generalizable by experts in the IT service management and enterprise architecture discipline. This paper contributes to enterprise modeling by demonstrating the feasibility of DESERV IT in an example case and describing DESERV IT’s evolution during the evaluation episodes. DESERV IT supports practitioners (e.g., request fulfillment managers) in modeling and analyzing IT services.

Large language models (LLM) are considered by many researchers as promising technology for automating routine tasks. Results from applying LLM in engineering disciplines such as Enterprise Modeling also indicate potential for the support of modeling activities. LLMs are fine-tuned for specific tasks using chat based interaction through the use of prompts. This paper aims at a detailed investigation of the potential of LLMs in Enterprise Modeling (EM) by taking the perspective of EM method adaptation of selected parts of the modeling process within the context of using prompts to interrogate the LLM. The research question addressed is: What adaptations in EM methods have to be made to exploit the potential of prompt based interaction with LLMs? The main contributions are (1) a meta-model for prompt engineering that integrates the concepts of the modeling domain under consideration with the notation of the modeling language applied and the input and output of prompts, (2) an investigation into the general potential of LLM in EM methods and its application in the 4EM method, and (3) implications for enterprise modeling methods.

Enterprise modeling is an important and widespread activity in managing enterprises. A well-founded conceptualization of its value is however missing so far which can be traced back to different understandings of constituents of enterprise modelling. Addressing these different understandings, we propose to take a service-centric perspective to determine the value of enterprise modelling. We describe the benefits of this perspective and justify our positioning regarding a service-centric perspective.

The need for organizations to operate in changing environments is addressed by proposing an approach that integrates organizational development with information system (IS) development taking into account changes in the application context of the solution. This is referred to as Capability Driven Development (CDD). A meta-model representing business and IS designs consisting of goals, key performance indicators, capabilities, context and capability delivery patterns, is being proposed. The use of themeta-model is validated in three industrial case studies as part of an ongoing collaboration project, whereas one case is presented in the paper. Issues related to the use of the CDD approach, namely, CDD methodology and tool support are also discussed.

Structuring enterprise information and supporting knowledge management is a growing application field for enterprise ontologies. Based on an industrial case from automotive supplier industries, the paper proposes the use of an ontology for artefact management in engineering of dependable systems, illustrated by the tool ArtefactManager. Navigation and search in the Artefact­Manager is performed using categorizations of artefacts by means of so-called taxonomic paths through the enterprise ontology. One of the main challenges is to permit evolution at least for those parts of the ontology which are used for categorizing artefacts. This paper introduces an approach to support the evolution process on the taxonomy level in conjunction with the level of categorizations.

Can large language models (LLMs) be used for digital twin engineering (DTE)? Engineering digital twins (DTs) is a complex process consisting of several phases and involving different disciplines. We argue that an investigation of LLM use in DTE has to define what kinds of DTs are in focus and what DTE phases shall be supported. In our work, we concentrate on the early phases of DTE, with a particular focus on requirements engineering (RE), and we focus on supervisory and operational DTs. This paper investigates the quality of LLM output for defining requirements for DTs. The main contributions of our work are results from an experiment comparing requirements to a DT of an air conditioning facility of a domain expert and ChatGPT and conclusions for prompt engineering resulting from this experiment. 

Due to the increasing implementation of agile and networked manufacturing, supply chain has entered a new phase, virtual supply chain. The phase is characterized by the integration of activities, operations, and functions carried out at different and geographically distributed supply chain stages. The paper proposes an approach to the configuration of a network of small and medium-sized enterprises (SMEs) being integrated into a supply chain. The SME supply chain configuration is based on a shared domain ontology for supply chain management, offering the configuration task as a function of supply chain management. Principles of the development of the shared ontology and possible ways of matching between enterprise and domain ontologies are considered.

In Software Engineering, patterns are an accepted way to facilitate and support reuse. This paper focuses on patterns in the field of Ontology Engineering and proposes a classification scheme for ontology patterns. The scheme divides ontology patterns into five levels: Application Patterns, Architecture Patterns, Design Patterns, Semantic Patterns, and Syntactic Patterns. Semantic and Syntactic Patterns are quite well-researched but the higher levels of pattern abstraction are so far almost unexplored. To illustrate the possibilities of patterns on

these levels some examples are discussed, together with ideas of future work.

High-quality and reusable ontologies are considered as key element of the Semantic Web and for successful semantic applications. Ontology Design Patterns (ODPs) are addressing these quality and reusability issues by providing different types of patterns supporting ontology designers. ODPs are collected in various repositories, such as the catalogue maintained by the University of Manchester and the ODP portal at small and do not cover all types of patterns and all domains. Semantic Web applications could also benefit from additional types of patterns, such as enterprise model patterns and specialized software patterns for semantic applications.

Patterns are an approach to knowledge reuse that proved feasible and very beneficial in various areas, such as software engineering and data modeling. Reuse has been an important research subject in ontology engineering and the semantic web community for many years. Patterns need to be shared by a community in order to provide a common language and stimulate pattern usage and development. Hence, the aim of this workshop was twofold

- providing an arena for proposing and discussing good practices, patterns, pattern-based ontologies, systems etc

- broadening the pattern community that will develop its own “language” for discussing and describing relevant problems and their solutions.

The workshop included a track for research papers addressing various aspects of ontology patterns and investigating application areas, and a pattern track focusing on presentation and discussion of actual ontology patterns.

Structuring enterprise information and supporting knowledge management is a growing application field for enterprise ontologies. Research work presented in this paper focuses on construction of enterprise ontologies. In an experiment, two methods were used in parallel when developing an ontology for a company in automotive supplier industries. One method is based on automatic ontology construction, the other method is a manual approach based on cookbook-like instructions. The paper compares and evaluates the methods and their results. For ontology evaluation, selected approaches were combined including both evaluation by ontology engineers and evaluation by domain experts. The main conclusion is that the compared methods have different strengths and an integration of both developed ontologies and used methods should be investigated.

Structuring enterprise information and supporting knowledge management is a growing application field for enterprise ontologies. Research work presented in this paper focuses on construction of enterprise ontologies. In an experiment, two methods were used in parallel when developing an ontology for a company in automotive supplier industries. One method is based on automatic ontology construction, the other method is a manual approach based on cookbook-like instructions. The paper compares and evaluates the methods and their results. For ontology evaluation, selected approaches were combined including both evaluation by ontology engineers and evaluation by domain experts. The main conclusion is that the compared methods have different strengths and an integration of both developed ontologies and used methods should be investigated.

IT operations aims to reduce the IT personnel’s workload in IT self-services, which is not self-evident. This study explores how the IT personnel’s workload can be reduced in IT self-services. A multiple-case study with five IT self-services was conducted. Data was collected from two German IT service providers and a European software company. The problem causing a non-reduction of the IT personnel’s workload in IT self-services is a lack of service production control and it is rooted in knowledge and skill gaps and a free IT self-service outcome. The two solutions to that problem comprise the adoption of five behavioral patterns: chargeback and limitation, standardization of the IT self-service, authorization of employee orders, showback, and training and support. This study is first revealing the mechanisms how IT self-services can be operated successfully from a service operations perspective.

Prior research has provided a number of approaches for the specification and analysis of service processes. However, little is known about their level of maturity regarding considered dimensions and characteristics. The present study represents a first step towards filling this gap. Drawing upon recent formalizations and delineations of service, a model for assessing the maturity of service modeling and analysis tools is derived. As part of a systematic literature review, it is applied to a set of 47 service blueprinting techniques to determine their maturity. The study’s findings indicate a high level of maturity regarding control flow and resource integration for most of the identified approaches. However, there are several shortcomings with respect to the input and output dimensions of the service process. The study proposes a set of research questions to stimulate future research and address the identified shortcomings.

This paper structures the summary of the panel held at the 9th International Conference on Enterprise Information Systems, Funchal, Madeira, 12-16 June 2007 that addressed the following question: "Are you still working on Inter-Enterprise Systems and Application Integration?" The panel aggregated distinguished experts from the areas of process management, workflow, Web services, SOA, and Semantic Web.

We discuss how an Enterprise Modelling approach, namely C3S3P, has been applied in an automotive supplier company. The paper concentrates on the phases of the C3S3P development process such as Concept Study, Scaffolding, Scoping, and Requirements Modelling. We have also presented the concept of task pattern which has been used in the MAPPER project for capturing, documenting and sharing best practices concerning business processes in organisation. Within this application context we have analysed our experiences concerning stakeholder participation and task pattern development.

Enterprise interoperability has been a research subject more than 2 decades and still offers numerous challenges for the scientific community. Based on an industrial case from automotive supplier industry and earlier work on variability modelling, this paper proposes to address enterprise interoperability by identifying correspondences and developing stepwise adjustment of enterprise models. The approach presented, called Connector Concept, puts equal focus on process and product knowledge when specifying interoperability requirements and has the long-term ambition to generate interfaces between IT-systems based on model integration. The main contributions of the work are (1) an initial method for connecting enterprise models of collaborating enterprises, (2) use of feature modelling for identification of interoperability requirements in product knowledge, and (3) an industrial case showing a concrete example and offering first experiences with the above approaches.

The work presented in this paper aims at contributing to enterprise interoperability. The focus is on collaboration in extended enterprises as general application field and active knowledge models as underlying technology. The starting point for the paper is an application case from automotive industry, where active knowledge models were developed for essential product development tasks. The paper concerns the development of a connector between these active knowledge models in order to support collaboration between two partners. The focus is on the operationalising phase of the connector development and on experiences. One result from this work is to propose three levels for the modeling, depending on the maturity level of the collaboration - searching for a partner, modeling existing collaboration and enhancing collaboration through detailed modeling.

We discuss how an Enterprise Modeling approach, namely C3S3P has been applied in an automotive supplier company. The chapter concentrates on the phases of the C3S3P development process such as Concept Study, Scaffolding, Scoping, and Requirements Modeling. We have also presented the concept of task pattern which has been used for capturing, documenting and sharing best practices concerning business processes in an organization. Within this application context we have analyzed our experiences concerning stakeholder participation and task pattern development. We have also described how we have derived four different categories of requirements from scenario descriptions for the task patterns and from modeling of the task patterns.

Current trends of globalisation and increased competition require new forms of organisation and work support. Especially in small and medium sized enterprises (SME), the competitiveness and future market position of an enterprise is closely related to the ability of cooperating with partners in SME networks or virtual supplier organisations. In complex work processes with a number of distributed partners, high requirements with respect to competence and a lot of rules and guidelines to be obeyed; detecting and sharing knowledge among different members of networked organizations is an important issue. Based on an empirical investigation regarding the demands of SME and illustrating this demand with industrial cases, this paper investigates two technical approaches supporting knowledge supply in networked organizations: enterprise modeling and self-organisation of flexible supply networks. These approaches are presented with related work and their limits and potentials.

Enterprise modeling (EM) is a discipline supporting business and IT alignment by providing means for capturing, visualizing and improving different perspectives of an enterprise, including processes,organization structures, products, systems, and business objectives. However, there is a lot of relevant information besides the one presented in enterprise models. Including such information into enterprise models or an integrated presentation of model and data view is supposed to ease decision making for stakeholders in organizations by providing contextual information for the decision at hand. Additional information however usually means additional complexity. This paper explores possibilities of an integrated presentation guided by the following questions: (1) What kind of complementary information should be visualized in an enterprise model?  (2) How can the information be visualized?  (3) How can the content of a specific visualization be adapted by the business stakeholder using it?

Possibilities and benefits of enhancing the existing enterprise models with visualization of additional information are illustrated using a small case study.

Enterprise knowledge modelling in general offers methods, tools and approaches for capturing knowledge about processes and products in formalized models in order to support organizational challenges. From the perspective of information systems development, the use of enterprise models traditionally is very strong in the earlier development phases, whereas approaches for applying enterprise models in later development phases exist, but are not as intensely researched and elaborated. We argue that enterprise models should be considered as carrier of enterprise knowledge, which can be used to a larger extent in creating actable solutions for enterprise problems. With competence supply as an example, the focus of the paper is on using enterprise models as interface for information searching. The main contributions of the paper are (1) to show that it is feasible and produces pertinent results to use enterprise models for expressing information demand, (2) architecture and implementation of an IT solution for this purpose and (3) lessons learned from validating this approach.

Managing and dealing with variability in business processes and the IT landscape is a common challenge in the everyday practice of most enterprises and organizations. Recent studies have observed that digital transformation, Internet-of-Things solutions and the introduction of artificial intelligence cause changes and challenges in enterprises that simultaneously require variability on several levels, for instance, business processes, data architecture, and services. Enterprise architecture models are considered a suitable way to visualize and manage dependencies between different levels of an enterprise. However, the management of variability in enterprise architectures has not received much attention in scientific research. This article† aims to contribute to a better understanding of future investigation needs. Using a systematic literature analysis, the article structures the existing research work in the field and examines real-world challenges of variability based on a case study. We argue that there is a need for new constructs in enterprise architecture models that allow for expressing dependencies between variations on different enterprise architecture layers.

Managing and dealing with variability is a common challenge in the daily practice of many enterprises and organizations. Recent studies have observed that digital transformation and artificial intelligence solutions lead to changes in enterprises that simultaneously require variability on several levels of an enterprise (for example, business processes, data architecture, and services). Enterprise architecture models are considered a suitable way to visualize and manage dependencies between different levels of an enterprise. Still, there is not much work on managing variability in enterprise architectures. This paper aims to structure the existing research work and tribute to a better understanding of future investigation needs. We argue that there is a need for new constructs in enterprise architecture models that allow for expressing dependencies between variations on different enterprise architecture levels.

Financial industries are undergoing a digital transformation of their products, services, overall business models. Part of this digitalization in banking aims at automating most of the manual work in payment handling and integrating the workflows of involved service providers. The focus of the work presented in this paper is on fraud discovery and steps to fully automate it. Fraud discovery in financial transactions has become an important priority for banks. Fraud is increasing significantly with the expansion of modern technology and global communication, which results in substantial damages for the banks. Instant payment (IP) transactions cause new challenges for fraud detection due to the requirement of short processing time. The paper investigates the possibility to use artificial intelligence in IP fraud detection. The main contributions of our work are (a) an analysis of problem relevance from business and literature perspective, (b) a proposal for technological support for using AI in fraud detection of instant payment transactions, and (c) a feasibility study of selected fraud detection approaches.